Automatic Reassembly of Document Fragments via Context Based Statistical Models

Automatic Reassembly of Document Fragments via Context Based Statistical Models (2003)

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by Kulesh Shanmugasundaram , Nasir Memon

Venue:	Context Based Statistical Models ACSAC, 2003
Citations:	13 - 2 self

BibTeX

@INPROCEEDINGS{Shanmugasundaram03automaticreassembly,
    author = {Kulesh Shanmugasundaram and Nasir Memon},
    title = {Automatic Reassembly of Document Fragments via Context Based Statistical Models},
    booktitle = {Context Based Statistical Models ACSAC, 2003},
    year = {2003},
    pages = {152--159}
}

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Abstract

Reassembly of fragmented objects from a collection of randomly mixed fragments is a common problem in classical forensics. In this paper we address the digital forensic equivalent, i.e., reassembly of document fragments, using statistical modelling tools applied in data compression. We propose a general process model for automatically analyzing a collection fragments to reconstruct the original document by placing the fragments in proper order. Probabilities are assigned to the likelihood that two given fragments are adjacent in the original using context modelling techniques in data compression. The problem of finding the optimal ordering is shown to be equivalent to finding a maximum weight Hamiltonian path in a complete graph. Heuristics are designed and explored and implementation results provided which demonstrate the validity of the proposed technique. 1.

Keyphrases

document fragment statistical model automatic reassembly data compression mixed fragment fragmented object classical forensics optimal ordering maximum weight hamiltonian path original document statistical modelling tool common problem collection fragment digital forensic equivalent proper order implementation result general process model complete graph